Route planning devices are well known in the field of navigational instruments. The method of route planning implemented by known prior art systems depends on the capabilities of system resources, such as processor speed and the amount and speed of memory. As increased system capability also increases system cost, the method of route planning implemented by a navigation device is a function of overall system cost.
Generally, with a navigational aid device, cartographic data is loaded into a memory of the device and manipulated to provide route planning to a user of the device. Selecting the optimal route can be processor and memory intensive since a variety of thoroughfare names, thoroughfare classifications, geographic distances between thoroughfares, time estimates between thoroughfares, and the like must be rapidly processed to provide near instantaneous route planning information to the user of the device. Moreover, as the memory and the processor performance demands increase to provide an acceptable level of processing throughput, the navigational device becomes more expensive for the user to purchase. Additionally, the physical dimensions of the device may increase and correspondingly the portability and attractiveness of the device becomes less appealing to the user.
Additionally, when a navigation device deviates from a provided route plan, the device preferably responds rapidly respond by projecting a new route plan which must be communicated to the user of the device quickly. Otherwise unless the device is completely stopped for some period of time, the device could deviate farther from the projected new route and the device could be rendered useless to the user. Of course, stopping may not be practical when the device is being used within a vehicle on the roadways.
Clearly, in many cases halting travel is not a viable alternative. For example, when the user is traveling on an interstate it is entirely impossible to simply stop. The alternative of pulling off on the shoulder is undesirable and can be dangerous. Pulling off on an exit is equally undesirable since doing so increases travel time and provides an added inconvenience to the user. In other instances, such as navigating downtown city streets, the traffic issues alone may prevent the user from stopping their vehicle during the recalculation process. Even if the user has the ability to safely stop their vehicle, such as when traveling in a neighborhood, the inconvenience factor is present. Accordingly, it is vitally important for the device to rapidly and often repetitively calculate a dynamic route plan for the device to reach a desired destination. To achieve this result, efficient memory and processor performance are critical.
A variety of techniques addressing a subset of the problem have attempted to alleviate memory and processor bottlenecks, such as requiring the user to load into the device's memory a selected geographic region by connecting the device to a remote storage having a desired region or by requiring the user to connect the device to a computing device and download the desired region from a remote location. Yet, cartographic data are voluminous and even with reduced region selections, current devices require substantial memory to efficiently generate a route plan for a user. Typically, to generate a route plan with a reasonable processor there must be at least 500 kilobytes of available random access memory (RAM), but more likely 2 megabytes or more of available RAM can be required.
In summary, current prior art systems have created a spectrum of products in which the processing throughput of the products is directly related to the capacity of the available RAM of the products. Further, as users demand products with greater functionality the problem continues to escalate proportionally. As a result, products are costly and becoming less portable due to an increase in their physical size.
Therefore, there exists a need for a navigational route planning device which is more efficient and accurate than current systems, without requiring the more expensive system resources, such as increased RAM capacity. In addition, there is also a need for a navigational route planning device which rapidly and efficiently generates a route plan.